MetaOmics: analysis pipeline and browser-based software suite for transcriptomic meta-analysis. Bioinformatics 2019 May 01;35(9):1597-1599
Date
10/12/2018Pubmed ID
30304367Pubmed Central ID
PMC6499246DOI
10.1093/bioinformatics/bty825Scopus ID
2-s2.0-85065663763 (requires institutional sign-in at Scopus site) 19 CitationsAbstract
SUMMARY: The rapid advances of omics technologies have generated abundant genomic data in public repositories and effective analytical approaches are critical to fully decipher biological knowledge inside these data. Meta-analysis combines multiple studies of a related hypothesis to improve statistical power, accuracy and reproducibility beyond individual study analysis. To date, many transcriptomic meta-analysis methods have been developed, yet few thoughtful guidelines exist. Here, we introduce a comprehensive analytical pipeline and browser-based software suite, called MetaOmics, to meta-analyze multiple transcriptomic studies for various biological purposes, including quality control, differential expression analysis, pathway enrichment analysis, differential co-expression network analysis, prediction, clustering and dimension reduction. The pipeline includes many public as well as >10 in-house transcriptomic meta-analytic methods with data-driven and biological-aim-driven strategies, hands-on protocols, an intuitive user interface and step-by-step instructions.
AVAILABILITY AND IMPLEMENTATION: MetaOmics is freely available at https://github.com/metaOmics/metaOmics.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Author List
Ma T, Huo Z, Kuo A, Zhu L, Fang Z, Zeng X, Lin CW, Liu S, Wang L, Liu P, Rahman T, Chang LC, Kim S, Li J, Park Y, Song C, Oesterreich S, Sibille E, Tseng GCAuthor
Chien-Wei Lin PhD Associate Professor in the Data Science Institute department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
Gene Expression ProfilingGenomics
Reproducibility of Results
Software
Transcriptome
